Triple

T1722002
Position Surface form Disambiguated ID Type / Status
Subject Airbus A300 E37411 entity
Predicate usedBy P260 FINISHED
Object Korean Air E30717 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Korean Air | Statement: [Airbus A300, usedBy, Korean Air]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Korean Air
Context triple: [Airbus A300, usedBy, Korean Air]
  • A. Korean Air chosen
    Korean Air is South Korea’s largest airline and flag carrier, operating extensive international and domestic passenger and cargo services worldwide.
  • B. Asiana Airlines
    Asiana Airlines is a major South Korean international airline based in Seoul, operating an extensive network of passenger and cargo services across Asia, Europe, North America, and Oceania.
  • C. Jin Air
    Jin Air is a South Korean low-cost airline that operates domestic and international passenger flights.
  • D. Asia Pacific Airlines
    Asia Pacific Airlines is a cargo and charter airline based in Guam that primarily serves destinations across Micronesia and the Western Pacific region.
  • E. Skymark Airlines
    Skymark Airlines is a Japanese low-cost carrier based in Tokyo that operates domestic flights and some international services.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a8861acab88190bb43cde203429399 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa635703dc8190809260de43b72ea3 completed March 6, 2026, 5:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada980ec888190b78726012e50c905 completed March 8, 2026, 4:53 p.m.
Created at: March 4, 2026, 7:30 p.m.